Characterizing Vision-Language-Action Models across XPUs: Constraints and Acceleration for On-Robot Deployment
Vision-Language-Action (VLA) models are promising for generalist robot control, but on-robot deployment is bottlenecked by real-time inference under tight cost and energy budgets. Most prior evaluations rely on desktop-grade GPUs, obscuring the trade-offs and opportunities offered by heterogeneous edge accelerators (GPUs/XPUs/NPUs). We present a systematic analysis for low-cost VLA deployment via model-hardware co-characterization. First, we build a cross-accelerator leaderboard and evaluate model-hardware pairs under CET (Cost, Energy, Time), showing that right-sized edge devices can be more cost-/energy-efficient than flagship GPUs while meeting control-rate constraints. Second, using i...
| Authors | Kaijun Zhou, Qiwei Chen, Da Peng et al. |
|---|---|
| Primary category | cs.RO |
| Published | 27 April 2026 |
| Last updated at source | 27 April 2026 |
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